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---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-bleeding-exp_0
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# videomae-base-finetuned-bleeding-exp_0
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4958
- Accuracy: 0.5
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.04 | 2 | 0.6967 | 0.5 |
| No log | 1.04 | 4 | 0.6799 | 0.75 |
| No log | 2.04 | 6 | 0.6721 | 0.75 |
| No log | 3.04 | 8 | 0.6742 | 0.75 |
| 0.6424 | 4.04 | 10 | 0.6927 | 0.25 |
| 0.6424 | 5.04 | 12 | 0.7295 | 0.5 |
| 0.6424 | 6.04 | 14 | 0.8047 | 0.5 |
| 0.6424 | 7.04 | 16 | 0.8589 | 0.5 |
| 0.6424 | 8.04 | 18 | 0.8842 | 0.5 |
| 0.6123 | 9.04 | 20 | 0.9349 | 0.5 |
| 0.6123 | 10.04 | 22 | 0.9543 | 0.5 |
| 0.6123 | 11.04 | 24 | 0.9924 | 0.5 |
| 0.6123 | 12.04 | 26 | 1.0729 | 0.5 |
| 0.6123 | 13.04 | 28 | 1.2268 | 0.5 |
| 0.3641 | 14.04 | 30 | 1.3759 | 0.5 |
| 0.3641 | 15.04 | 32 | 1.4344 | 0.5 |
| 0.3641 | 16.04 | 34 | 1.4563 | 0.5 |
| 0.3641 | 17.04 | 36 | 1.4365 | 0.5 |
| 0.3641 | 18.04 | 38 | 1.4343 | 0.5 |
| 0.4378 | 19.04 | 40 | 1.4375 | 0.5 |
| 0.4378 | 20.04 | 42 | 1.4530 | 0.5 |
| 0.4378 | 21.04 | 44 | 1.4732 | 0.5 |
| 0.4378 | 22.04 | 46 | 1.4877 | 0.5 |
| 0.4378 | 23.04 | 48 | 1.4919 | 0.5 |
| 0.222 | 24.04 | 50 | 1.4958 | 0.5 |
### Framework versions
- Transformers 4.40.2
- Pytorch 1.12.0
- Datasets 2.19.1
- Tokenizers 0.19.1
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